Technical Field
The disclosure relates to a system, a method and a recording medium for calculating a physiological index.
Related Art
Using information technology to collect various physiological signals and analyze physiological heath status of an individual case is a joint collaborative research topic for the fields of medical care and information science. For example, analysis of an electrocardiogram (ECG) signal has been a very important issue in analysis of cardiovascular-related diseases, because it can directly reflect the status of heart function.
Most signs of diseases will show slight differences in the variability of operation and rhythm of physical organs, although many international companies and medical researchers have provided processes and methods for monitoring and analyzing the physiological signal, there are still some technical problems to be solved.
Taking the ECG as an example, current heart function examination mainly uses short-term ECG analysis. As many diseases cannot be detected from short-term ECG, researchers have developed physiological indexes that are mainly obtained by analyzing the complexity of the heart rhythm from the multi-scale perspective using long-term ECG in recent years. It is verified in researches that this type of indexes can exactly reflect the health status of the heart function. Calculation of multi-scale physiological index is more complex than the conventional statistical analysis of time-frequency domain, especially the effectiveness of multi-scale entropy (MSE) based on entropy has been proven in medical researches.
Although the long-term ECG analysis can provide complete physiological information of an individual case, the system needs a large space for storing long-term ECG data. How to design a new mechanism that can efficiently store the ECG information while calculating a long-term ECG physiological index is one of the challenges in long-term ECG analysis.
The long-term physiological index that is developed based on multiple scales can present a physiological state of an individual case in a long-term range, but the difference of the physiological state cannot be obtained through analysis of a short-term physiological signal. However, due to a considerable computation time, the application of long-term physiological index is restricted in interpretation of and research of symptoms after an individual case is attacked, and is not applied in monitoring and early warning of a physiological state of an individual case. It can be seen that, how to enable this type of multi-scale physiological indexes to have the capability of monitoring and evaluating the physiological state of an individual case in real time as far as possible is a very important issue in physiological monitoring of an individual case in clinic.